The metabolic syndrome is a complex clustering of cardiometabolic abnormalities associated with aging, physical inactivity, and abdominal adiposity (5,12,18). Globally, the incidence of the metabolic syndrome and its associated increase in cardiometabolic risk have reached pandemic proportions. Of the risk factors used to identify the metabolic syndrome, elevated abdominal visceral fat (AVF) has consistently been shown to be associated with increased cardiometabolic risk (30). The International Diabetes Federation (IDF) consensus statement (2) identified central obesity as the unifying cardiometabolic risk factor among individuals with the metabolic syndrome. Researchers and clinicians worldwide are intensively investigating both pharmacological and nonpharmacological approaches to reduce visceral adiposity and its related comorbidities.
Exercise training provides an economically viable, nonpharmacological approach for eliciting beneficial adaptations in body composition and cardiometabolic risk. In support of this contention, endurance training has been shown to be a powerful strategy for inducing abdominal fat loss, particularly with respect to AVF loss (16,23,27,31). Despite much interest in exercise-induced fat loss, the optimal exercise prescription to maximize fat loss remains elusive. Only a limited number of exercise interventions have systematically examined the impact of endurance training intensity on fat loss and, in particular, AVF loss under equivalent energy expenditures (36,37). It may be postulated that high-intensity exercise training (HIET) may induce greater fat loss, in particular, AVF loss, than low-intensity exercise training (LIET) for several reasons. First, HIET induces secretion of lipolytic hormones, including growth hormone and epinephrine (32,33), which may facilitate greater postexercise energy expenditure and fat oxidation. Second, it has been reported that under equivalent levels of energy expenditure, HIET favors a greater negative energy balance compared with LIET (21). In the present study, we examined the impact of endurance training intensity on AVF under equivalent caloric expenditure (2000 kcal·wk−1). We hypothesized that 16 wk of endurance training above the lactate threshold (LT; i.e., HIET) would result in a greater reduction in AVF and more favorable changes in body composition than 16 wk of endurance training below the LT (i.e., LIET) in abdominally obese women with the metabolic syndrome.
Twenty-seven middle-aged women (mean ± SD; 51 ± 9 yr) who met the IDF criteria for the metabolic syndrome (2) completed the present study. To meet the IDF criteria for the metabolic syndrome, each participant had to have an elevated waist circumference (≥80 cm) and at least two of the following: elevated fastingblood glucose (≥100 mg·dL−1), low HDL-C (≤50 mg·dL−1), hypertriglyceridemia (≥150 mg·dL−1), and/or elevated blood pressure (≥130/85 mm Hg) (2). The participants were sedentary at baseline, reporting less than 2 d·wk−1 of structured exercise. All participants underwent an initial eligibility screening in the University of Virginia's General Clinical Research Center (GCRC; see below). The Institutional Review Board, Human Investigation Committee of the University of Virginia's Health System approved this study, and each participant provided written informed consent.
Metabolic syndrome and medical screening protocol.
Participants reported to the GCRC for screening after a 10- to 12-h fast at ∼0900 h. Participants provided a detailed medical history and underwent a physical examination, which included an assessment of the five risk factors associated with the metabolic syndrome as defined by the IDF (2). In brief, waist circumference measurements were taken in triplicate to the nearest 0.1 cm using a nonelastic measuring tape midway between the iliac crest and the lowest rib (28). Seated blood pressure was assessed in duplicate using an automated sphygmomanometer (Dynamap 100; General Electric, Tampa, FL) after participants sat quietly for 10 to 15 min. Fasting blood samples were then drawn, and serum was separated by centrifugation. Glucose, triglycerides, and HDL-C concentrations were assessed inserum. Glucose concentrations were determined by usingan automated glucose analyzer (2300 STAT Plus; Yellow Springs Instruments (YSI), Yellow Springs, OH). Triglycerides and HDL-C concentrations were determined using an automatic analyzer (Olympus AU640; Olympus, Melville, NY). All participants were asked to refrain from caffeine, alcohol, and vigorous physical activity for 24 h before testing. Exclusion criteria included a history of ischemic heart disease, diabetes, or pulmonary or musculoskeletal limitations to exercise; the use of vasoactive medications, oral hypoglycemics, insulin, glucocorticoids, antipsychotics, hormone replacement; or birth control and if pregnant, breast feeding, or unwilling to provide written informed consent.
Eligible participants were randomized to one of three 16-wk exercise training conditions: (i) no-exercise training (Control), (ii) LIET, or (iii) HIET. Figure 1 presents the distribution of study participants. Participants were assessed before and after the 16-wk intervention. Participants were admitted to the GCRC for 2 d during which the following evaluations were performed (see below). The one exception was the cardiorespiratory fitness assessment that was conducted as an outpatient visit. To control for the effects of menstrual cycle on outcome variables, premenopausal women were admitted between days 2 and 8 of their menstrual cycle. Postmenopausal status was determined by the absence of menses for >1 yr. In the no-exercise training condition, there was one premenopausal woman, one woman who underwent a hysterectomy (menopausal status unknown), and five postmenopausal women; in the LIET condition, there were three premenopausal women, four women who underwent a hysterectomy (menopausal status unknown), and four postmenopausal women; and in the HIET condition, there were two premenopausal women, two women who underwent a hysterectomy (menopausal status unknown), and seven postmenopausal women. Participants were asked to refrain from alcohol, caffeine, and cigarette smoking for at least 72 h before their admission.
Body composition assessment.
Body composition was measured using air displacement plethysmography (Bod-Pod; Life Measurement Instruments, Concord, CA) corrected for thoracic gas volume as described previously (7).
Single-slice computed tomography (CT) images were obtained at the level of L4-L5 intervertebral disc space and at the midpoint between the inguinal crease and the top of the patella as previously described (22). All scans were performed using a CT scanner (Lightspeed; GE Medical Systems, Milwaukee, WI) and saved as DICOM images for analysis. Standard CT procedures of 120-kV, 5-mm thickness, and a 512 × 512 matrix were used for all subjects. A single trained investigator analyzed each of the blinded CT images using the Slice-O-Matic version 4.3 software package (TomoVision, Montreal, Canada) for the delineation and quantification of cross-sectional areas of fat, muscle, and bone as previously described (22,29). The measurement boundary for AVF was defined as the innermost aspect of the abdominal and oblique muscle walls and the posterior aspect of the vertebral body as described previously (6). In addition, we also quantified abdominal subcutaneous fat area at the L4-L5 intervertebral disc space. At the midthigh, we assessed the total midthigh fat area and the total midthigh skeletal muscle area. The inter- and intrainvestigator coefficient of variations for these analyses in our laboratory are less than 5% (22).
Cardiorespiratory fitness assessment.
Participants completed a continuous V˙O2peak treadmill protocol. The initial treadmill (Model Q65; Quinton Instrument Co, Seattle, WA) velocity was 60 m·min−1, and the velocity was increased by 10 m·min−1 every 3 min until volitional fatigue. Metabolic data were collected during the protocol using standard open-circuit spirometric techniques (Vmax 229; Viasys Healthcare, Yorba Linda, CA), and heart rate was assessed electrocardiographically (Marquette Max-1; Marquette Medical Systems, Inc, Marquette, WI). V˙O2peak was chosen as the highest V˙O2 attained during the exercise protocol. An indwelling venous cannula was inserted in a forearm vein, and blood samples were taken at rest and at the end of each exercise stage for the measurement of blood lactate concentration (2300 STAT Plus; YSI). The LT was determined from the blood lactate-velocity relationship and was defined as the highest velocity attained before the curvilinear increase in blood lactate concentrations above baseline (43). A lactate elevation of at least 0.2 mmol·L−1 (the error associated with the lactate analyzer) was required for LT determination. Individual plots of V˙O2 versus velocity allowed for the determination of the V˙O2 associated with the LT. RER, heart rate, and blood lactate responses were monitored to ensure that participants attained peak values at the point of volitional exhaustion. V˙O2peak was chosen as the highest V˙O2 attained during the test.
Physical activity and dietary assessment.
The time spent in physical activity at different intensities was assessed using the Aerobic Center Longitudinal Study's Physical Activity Questionnaire (26). The questionnaire was administered using an interview technique to increase accuracy (34). Total physical activity was calculated as MET-hours per week (1 MET = 3.5 mL·kg−1·min−1) using the compendium of physical activities (1). Participants were instructed by a registered dietician on how to complete a 3-d dietary record that was analyzed using a commercially available nutrition software program (The Food Processor SQL; ESHA Research, Salem, OR).
Basal metabolic rate.
After an overnight fast, participants were awakened at 0600 h, asked to void, return to bed, and remain awake in the supine position for 30 min in a quiet and thermoneutral environment. Basal metabolic rate (BMR) was measured by indirect calorimetry (Delta Trac metabolic cart and ventilation hood; SensorMedics, Yorba Linda, CA) for 30 min.
Participants were randomized to one of the following three interventions: (i) no-exercise training, (ii) LIET, or (iii) high-intensity.
- (i) No-Exercise Training (Control). Participants maintained their current level of physical activity for the duration of the study.
- (ii) LIET. Participants completed a 16-wk supervised low-intensity exercise intervention. Participants were progressed to complete five exercise sessions (days) per week by week 5 at an intensity at or below their LT (RPE ∼10-12). The duration of each exercise session was adjusted on the basis of each participant's individual V˙O2-velocity relationship so that each participant expended a total of 300 kcal per training session for weeks 1-2 (3 d·wk−1), 350 kcal per session for weeks 3-4 (4 d·wk−1), and 400 kcal per session for weeks 5-16 (5 d·wk−1). As each participant's fitness level improved, the velocity required to maintain her assigned RPE was increased; therefore, the duration was readjusted to maintain the kilocalorie requirement. Exercise was prescribed on the basis of the rating of perceived exertion obtained during the LT/V˙O2peak protocol, and one of the investigators monitored RPE during each training session.
- (iii) HIET. Participants completed a 16-wk supervised moderate- to high-intensity exercise intervention. Participants were progressed to five exercise sessions (days) per week by week 5. Three days per week (e.g., M, W, F), participants exercised at an intensity midway between the LT and the V˙O2peak (RPE ∼15-17), and on the remaining 2 d (e.g., T, Th), they exercised at or below their LT (RPE ∼10-12). The progression of caloric expenditures and the velocity and duration adjustments were made as described for LIET, with the exception that participants always had 3 d·wk−1 > LT and 1 d·wk−1 < LT training session was added at week 3 and again at week 5.
All exercise training sessions were supervised by a member of the investigative team and took place at the University of Virginia indoor or outdoor track. Each participant was instructed to walk/run the distance associated with her prescribed caloric expenditure on the basis of each participant's body weight and associated caloric output from the compendium of physical activity. If participants lost weight, the distance required to expend a given energy expenditure increased accordingly. For example, a 90-kg woman would complete 3.5 miles per session to expend 400kcal per session, whereas an 80-kg woman would complete 4.0 miles per session.
The rationale for using RPE as an index of training intensity comes from our previous data that suggest that RPE is an accurate marker of the blood lactate response toexercise that is not affected by gender, fitness, training state, mode of exercise, or intensity of training (20,35,38) and that RPE can be used to produce a desired blood lactate concentration during 30 min of treadmill running (38). In addition, Jakicic et al. (24) reported that RPE provide amore accurate marker of relative exercise intensity compared with the percentage of heart rate reserve in obese women before and after weight loss. Each participant's RPE was monitored on a lap-by-lap basis to assess the prescribed exercise intensity, and the velocities required to maintain the assigned RPE were adjusted accordingly. Heart rate data were not collected during the exercise sessions; however, as stated above, RPE have been shown to be an accurate marker of relative exercise intensity among obese adults.
All statistical analyses were conducted using SAS software (version 9.1; SAS Institute, Cary, NC). Because measurements of the responses at 16wk were required for the participant to be included in the analysis, our target study population with respect to statistical inference was the population of individuals who met the study inclusion criteria and who successfully completed the 16-wk intervention. The frequency of patient dropouts was analyzed across the three interventions to determine whether the dropout rate was at random or whether it was associated with the participants' treatment assignment. Data are presented as means ± SD.
The present study was powered to detect a ∼30-cm2 reduction in AVF (ΔAVF = baseline − 16-wk AVF measurement) with 12 participants per group. Two-way, mixed-effects ANCOVA was used to examine mean differences in pre- to posttraining values (14). The model specification included parameters to estimate the exercise intensity main effect (Control, LIET, and HIET), the time main effect (pre- and posttraining), and their interaction effect on the change in the dependent variables. Their baseline value served as the covariate. In addition, the model included random effects that represented the between- and within-subject error terms. The model parameters were estimated on the basis of the principles of restricted maximum likelihood, with the variance-covariance structure estimated using unstructured estimate. For all analyses, pairwise comparisons of the means were conducted when the main effect of group or time or the interaction between group and time was significant. Fisher's restricted least significant differences criterion was used to maintain the a priori type I error rate of 0.05. In addition, we conducted ANCOVA using menopausal status as a covariate (data not shown). Because we did not observe any significant effects of menopausal status on any of the outcome measures, group data are presented. Spearman rank correlations were calculated to test the association among changes in weight, fat mass, waist circumference, and metabolic syndrome parameters.
Pretraining characteristics and exercise adherence.
Tables 1-3 present the mean ± SD pre- and posttraining values for the metabolic syndrome parameters, body composition, cardiorespiratory fitness, physical activity, and BMR by treatment condition. There were no significant differences among the three conditions at baseline for any outcome measure (all P > 0.1; Tables 1-3). Table 4 presents the summary data for exercise adherence, volume, and intensity. Both the LIET and the HIET groups had similar exercise adherence, with ∼79 ± 3% and ∼83 ± 3% of the assigned exercise sessions completed within each exercise condition, respectively. We did not observe a differential rate in dropouts among the three conditions (Fig. 1). During LIET exercise sessions, the mean RPE was ∼11; for HIET, the mean RPE was ∼15 during the HIET sessions and ∼12 during the LIET sessions. By design, the mean velocity per session and the mean RPE per session were significantly higher in the HIET group during their HIET days compared with the LIET group. There were no statistically significant differences between the two training groups for the total estimated caloric energy expenditure.
Metabolic syndrome parameters.
By design, all participants had elevated waist circumference and at least two of the following: had elevated fasting blood glucose, had low HDL-C, had hypertriglyceridemia, and were normotensive to mildly hypertensive at baseline (Table 1). HIET significantly reduced waist circumference (P = 0.001), which was significantly greater than the reductions observed in response to Control and LIET (P = 0.039 and P= 0.035, respectively; Table 1) after adjusting for the baseline values. LIET significantly reduced systolic blood pressure (P = 0.002), which was significantly greater than the reduction observed in response to Control (P = 0.023; Table 1) after adjusting for the baseline values. However, the remaining metabolic syndrome parameters remained unchanged.
HIET significantly reduced total abdominal fat (P < 0.001, Table 2), AVF (P = 0.010; Table 2 and Fig. 2C), and abdominal subcutaneous fat (P = 0.034; Table 2 and Fig. 2D) after adjusting for the baseline values. There were no significant changes observed in any of these parameters within the Control or the LIET conditions. The reductions in total abdominal fat and abdominal subcutaneous fat cross-sectional areas in the HIET condition were significantly greater than those observed in the LIET condition (P = 0.017 and P = 0.033, respectively) after adjusting for the baseline values. Although the reduction in AVF within HIET condition (−24 cm2) was much greater than that observed within the Control condition (−2 cm2) and the LIET condition (−7 cm2), these differences did not reach the level of statistical significance across conditions (P = 0.098 and P = 0.153, respectively). HIET also significantly reduced total midthigh fat (P = 0.001; Table 2 and Fig. 2E). We did not observe a significant change in total midthigh skeletal muscle among the three treatment conditions (P > 0.1; Table 2 and Fig. 2D). HIET significantly reduced total body weight (P = 0.013), body mass index (BMI; P = 0.009), and fat mass (P = 0.011; Table 2).
LIET and HIET significantly elevated V˙O2peak (P = 0.047 and P = 0.004, respectively; Table 3). The increase in V˙O2peak in the HIET condition exceeded that for Control and LIET conditions (P= 0.016 and P = 0.078, respectively; Table 3). V˙O2 LT was unchanged after training in all three conditions (all P > 0.1; Table 3). LIET and HIET resulted in significant elevations in peak treadmill velocity (P = 0.006 and P < 0.001, respectively; Table 3). HIET induced a greater elevation in peak treadmill velocity than Control and LIET (P = 0.005 and P = 0.056, respectively; Table 3).
BMR, physical activity, and diet.
We did not observe any significant changes in the BMR (Table 3) or substrate oxidation assessed using the basal RER (data not shown). We also did not observe any significant changes in total physical activity in response to the three treatment conditions (Table 3). A limitation of the present study isthat due to incomplete dietary data, we were unable to adequately analyze the dietary records for pre- to posttraining changes in caloric intake.
Spearman correlation analyses.
Pooled Spearman correlation analyses (N = 27) were conducted to examine the relationships among pre- to posttraining changes weight, percent fat, AVF, and the metabolic syndrome parameters. Weight loss was positively associated with reductions in triglycerides (r = 0.56, P = 0.002) and SBP (r = 0.44, P = 0.022). Fat mass loss was also positively associated with (r= 0.49, P = 0.009) triglycerides.
Published data on the effect of exercise training intensity on body composition and regional body fat are mixed (4,15,17,27,36,41). With regard to total body fat loss, total caloric expenditure seems to be the key factor (4,15,17,37). Slentz et al. (37) reported that low-amount/moderate-intensity and low-amount/vigorous-intensity endurance training (i.e., activity equivalent to ∼12 miles·wk−1 of walking or jogging) were equally effective in reducing percent body fat, fat mass, waist circumference, and abdominal circumference in previously sedentary, overweight, middle-aged adults. They also reported that high-amount/vigorous-intensity endurance training (activity equivalent to ∼20 miles·wk−1 of jogging) was more effective in reducing percent body fat and fat mass compared with the two low-amount training groups (37). Although the exercise intensity was not equated across training volumes, the authors did effectively demonstrate a dose-response relationship between training volume and amount of weight change using a pooled analysis (37).
Our results suggest that HIET may be an effective stimulus for inducing favorable changes in body composition. Specifically, HIET significantly reduced body weight, BMI, percent body fat, fat mass, and waist circumference (Table 1). Our results are consistent with those of Tremblay et al. (42) who reported that high-intensity intermittent exercise training induced greater subcutaneous fat loss compared with moderate-intensity exercise training under isocaloric training conditions. Similarly, Tremblay et al. (41) also reported results from the Canadian Fitness Survey that indicated that vigorous physical activity was associated with lower subcutaneous skinfold thickness, which continued to remain significant after adjusting for total energy expenditure. It should be realized that HIET was likely associated with slightly greater exercise energy expenditure and total energy expenditure than LIET. The kilocalorie pertraining session was based on total energy expenditure (e.g., 300, 350, or 400 kcal per session), and the resting metabolism was part of the total. Therefore, on the high-intensity exercise days where duration was ∼6 min shorter (Table 4), resting metabolism would contribute to a lower fraction of the total energy expenditure. This resulted in an approximately 400-kcal difference in exercise energy expenditure between the high- and the low-intensity groups over the 16-wk time frame (∼25 kcal·wk−1). In addition, it is likely that postexercise oxygen consumption was higher on the HIET days.
In view of the previous work and the present findings, an interaction between exercise intensity and training volume may exist with respect to changes in body composition. Further investigations are warranted to examine the interaction between training volume and intensity on changes in body composition.
Regional body fat.
Exercise training, even in the absence of weight loss, is associated with a significant reduction in AVF (27). Whether intensity of exercise is an important training variable for inducing reductions in AVF is not clear, although data on responses to acute exercise suggest that higher-intensity exercise may be more effective than low- to moderate-intensity exercise for mobilizing AVF by inducing secretion of lipolytic hormones, facilitating greater postexercise energy expenditure and fat oxidation, and by favoring a greater negative energy balance (21,32,33). Our results indicate that HIET is an effective exercise abdominal subcutaneous fat (−47 vs −11cm2, adjusted for baseline) and AVF (−24 vs −7 cm2, adjusted for baseline). Data from Slentz et al. (36), however, suggest that low-amount/moderate-intensity orlow-amount/vigorous-intensity exercise training was equally effective in preventing significant increases in AVF associated with continued physical inactivity in sedentary, overweight, middle-aged adults under isocaloric conditions. These authors also reported a significant reduction in AVF in subjects who completed 8 months of high-amount/vigorous-intensity exercise training (activity equivalent to ∼20 miles·wk−1 of jogging), indicating that training volume may play a critical factor in exercise-induced AVF loss (36). However, by not including a high-amount/moderate-intensity exercise training group, the authors eliminated the opportunity to determine whether an interaction between training volume and training intensity exists for AVF loss. The training volume in the present study was equated across training conditions and was similar to the training volume in the high-amount/vigorous-intensity training condition reported by Slentz et al. (36). Taken together, these data suggest that an interaction between training volume and training intensity may exist for AVF loss.
BMR, physical activity, and diet.
Reported total physical activity and BMR remained unchanged. Unfortunately, due to incomplete dietary data, we were unable to adequately analyze changes in caloric intake and composition. Although several studies suggest that some women gain weight (and body fat) in response to exercise training, most of these studies have used low- to moderate-intensity exercises (8,11). The present data indicate that exercise training above the LT (i.e., HIET) may be an effective exercise intensity for inducing weight loss in obese women. Although not measured, it is also likely that HIET resulted in increased postexercise energy expenditure, which in turn was related to lower body fat deposition (44).
The present results demonstrate that endurance training intensity does not significantly impact exercise adherence. The primary reasons given for missing exercise sessions in the present cohort were related to time conflicts and personal travel. As the mean (and median) exercise adherence was ∼80%, 4 d of structured endurance training (at ∼1600 kcal·wk−1) seems to be a more realistic goal in this cohort of obese women with the metabolic syndrome. All participants were encouraged to make up their missed training sessions when possible, and the participants in the HIET condition were encouraged to complete all three HIET sessions per week. Four days per week (at ∼1600 kcal·wk−1) of endurance training would still remain within the current recommendations (19). It is also important to realize that the HIET was a blend of LIET (2 d·wk−1) and HIET (3 d·wk−1) and that participants were allowed to initially complete the HIET sessions in an "interval/intermittent"-type fashion. For example, for the first few laps of each training session, some subjects would perform one lap at an RPE of 16-17 and the subsequent lap at an RPE of 13-14, with the majority of the laps performed at an RPE ≥ 15. Moreover, the overall mean RPE for each HIET session was ≥15. The present results also demonstrate that even very sedentary, unfit, obese women (people) can adhere to a supervised program incorporating HIET.
Epidemiological data indicate that elevations in cardiorespiratory fitness (i.e., V˙O2peak) are associated with an attenuation cardiometabolic risk among individuals with the metabolic syndrome (25). It is well established that endurance training intensity is a primary determinant for exercise-induced improvements in cardiorespiratory fitness (3). HIET increased V˙O2peak more than LIET did (∼14% vs ∼9%), and this difference approached statistical significance after 16 wk (Table 1). It is possible that larger-intensity-related differences in V˙O2peak enhancement may take longer than 4 months in previously sedentary adults. We previously reported that training-induced elevations in V˙O2peak and V˙O2 at the LT in response to training at or above the LT were similar across the first 4 months of training in previously sedentary women (43). However, training above the LT was more effective than training at the LT beyond 4 months (43).
Metabolic syndrome parameters.
Despite significant improvements in body composition, including significant reductions in waist circumference and AVF, within the HIET condition, the improvement in some cardiometabolic risk factors associated with the metabolic syndrome (e.g., increased HDL-C, decreased TG) did not reach statistical significance and did not seem to be related to exercise training intensity. However, the present study was powered for changes in body composition and not for cardiometabolic risk factors. As expected, exercise training induced reductions in resting blood pressure. Typically, training-induced reductions in resting blood pressure are reported to be independent of training intensity (13). The significantly greater reduction in systolic blood pressure after LIET may have been due in part to the higher initial value, because baseline blood pressure seems to be an important factor in the blood pressure response to exercise (13). However, covarying for the baseline systolic blood pressure did not attenuate the effect of LIET on systolic blood pressure.
Spearman correlation analyses.
Weight loss was associated with reductions in triglycerides and systolic blood pressure, whereas fat loss was only associated with reductions in triglycerides. Although not statistically significant, AVF loss was associated with the expected reductions in triglycerides. The nonsignificant associations between AVF loss and metabolic syndrome components (i.e., fasting glucose, HDL-C, triglycerides, and systolic and diastolic blood pressures) indicate that it might take a greater AVF loss in our abdominally obese cohort to observe significant improvements in these parameters. For example, recent data from Thamer et al. (39) indicated that subjects with high AVF and high liver fat have a reduced chance in profiting from lifestyle intervention and suggested that they may require intensified lifestyle intervention strategies and/or pharmacological approaches to improve the metabolic profile. Moreover, it has been previously reported that individuals with excessive AVF (e.g., >130 cm2) often develop these cardiometabolic risk factors (9,10). Because the mean baseline AVF cross-sectional area for each exercise condition was substantially elevated (>153 cm2) and, although reduced as a result of training, was still well above 130 cm2 (>146 cm2), it is possible that greater reductions in AVF may be required to observe favorable changes in these metabolic syndrome parameters.
We recognize that a potential limitation of the present study is that the subjects in the HIET group tended to have slightly higher levels of AVF at the onset of the study. However, adjusting for baseline levels of AVF did not significantly attenuate the impact that HIET had on AVF. It has been previously reported that the use of single-slice images to measure changes in AVF is less precise than multislice images (40) and therefore may also be a limitation of the present study. However, a more precise measurement of the change in AVF likely would have resulted in narrower 95% confidence intervals and significant between-group differences with respect to the change in AVF. Although the present study was initially powered to detect significant changes in the AVF (∼30 cm2) with 12 participants per group, the present study did not achieve this level of recruitment because the number of dropouts exceeded our original estimation. However, despite this limitation, we did observe a statistically significant improvement in body composition (including AVF) within the HIET condition. Finally, due to incomplete dietary data, we were not able to adequately analyze the impact of reduced caloric intake on the changes in body composition. It has also been suggested that the use of RPE for exercise prescription may be a limitation. For example, when subjects know they are supposed to exercise at an RPE of 15-17 but they do not want to exercise that vigorously, this is a circumstance that may be prone to inflating a given RPE. However, the training program used did result in differentiated training effects for V˙O2peak and peak treadmill velocity. Finally, due to the issues related to statistical power, it is possible that some variables would have reached the level of statistical significance if more subjects had been studied. Thus, the nonsignificant results presented need to be interpreted with caution.
The results of the present investigation support our primary hypothesis that HIET would be more effective than LIET for altering body composition in obese women with the metabolic syndrome. Further investigations are warranted to determine the impact of training duration, gender, race, age, and menopausal status on modulating theeffect that exercise training intensity has on AVF and associated cardiometabolic risk factors.
The authors thank the staff of the GCRC at the University of Virginia and all of the subjects who participated enthusiastically in the study. The authors also thank James T. Patrie for useful discussions on statistical considerations. The present study was funded in part by an NIH grant to the General Clinical Research Center RR MO100847 and by NIH training grant 5T32AT00052. The results of the present study do not constitute endorsement by the ACSM. The authors have no other financial disclosures to declare.
Present address for B. A. Irving: Endocrine Research Unit, Mayo Clinic, Rochester, MN.
Present address for D. W. Brock: School of Public Health, University of Alabama Birmingham, Birmingham, AL.
Present address for C. K. Davis: School of Medicine, University of California at San Diego, San Diego, CA.
1. Ainsworth BE, Haskell WL, Whitt MC, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc
. 2000;32(9 Suppl):S498-504.
2. Alberti KG, Zimmet P, Shaw J. Metabolic syndrome-a new world-wide definition. A consensus statement from the International Diabetes Federation. Diabet Med
3. American College of Sports Medicine. ACSM's Guidelines for Exercise Testing and Prescription
. 7th ed. Philadelphia (PA): Lippincott Williams & Wilkins; 2006. 366 p.
4. Ballor DL, McCarthy JP, Wilterdink EJ. Exercise intensity does not affect the composition of diet- and exercise-induced body mass loss. Am J Clin Nutr
5. Carr DB, Utzschneider KM, Hull RL, et al. Intra-abdominal fat is a major determinant of the National Cholesterol Education Program Adult Treatment Panel III criteria for the metabolic syndrome. Diabetes
6. Clasey JL, Bouchard C, Wideman L, et al. The influence of anatomical boundaries, age, and sex on the assessment of abdominal visceral fat. Obes Res
7. Dempster P, Aitkens S. A new air displacement method for the determination of human body composition. Med Sci Sports Exerc
8. Despres JP, Bouchard C, Savard R, Tremblay A, Marcotte M, Theriault G. The effect of a 20-week endurance training program on adipose-tissue morphology and lipolysis in men and women. Metabolism
9. Despres JP, Lemieux I, Dagenais GR, Cantin B, Lamarche B. HDL-cholesterol as a marker of coronary heart disease risk: the Quebec cardiovascular study. Atherosclerosis
10. Després J-P, Moorjani S, Lupien PJ, Tremblay A, Nadeau A, Bouchard C. Regional distribution of body fat, plasma lipoproteins, and cardiovascular disease. Arteriosclerosis
11. Donnelly JE, Hill JO, Jacobsen DJ, et al. Effects of a 16-month randomized controlled exercise trial on body weight and composition in young, overweight men and women: the Midwest Exercise Trial. Arch Intern Med
12. Facchini FS, Hua N, Abbasi F, Reaven GM. Insulin resistance as a predictor of age-related diseases. J Clin Endocrinol Metab
13. Fagard RH. Exercise characteristics and the blood pressure response to dynamic physical training. Med Sci Sports Exerc
. 2001;33(6 Suppl):S484-92; discussion S93-4.
14. Fitzmaurice GM, Laird NM, Ware JH. Applied Longitudinal Analysis
. Hoboken (NJ): Wiley-Interscience; 2004. xix, 506 p.
15. Gaesser GA, Rich RG. Effects of high- and low-intensity exercise training on aerobic capacity and blood lipids. Med Sci Sports Exerc
16. Giannopoulou I, Ploutz-Snyder LL, Carhart R, et al. Exercise is required for visceral fat loss in postmenopausal women with type 2 diabetes. J Clin Endocrinol Metab
17. Grediagin A, Cody M, Rupp J, Benardot D, Shern R. Exercise intensity does not effect body composition change in untrained, moderately overfat women. J Am Diet Assoc
18. Grundy SM, Brewer HB Jr, Cleeman JI, Smith SC Jr, Lenfant C. Definition of metabolic syndrome: report of the National Heart, Lung, and Blood Institute/American Heart Association conference on scientific issues related to definition. Circulation
19. Haskell WL, Lee IM, Pate RR, et al. Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc
20. Hetzler RK, Seip RL, Boutcher SH, Pierce E, Snead D, Weltman A. Effect of exercise modality on ratings of perceived exertion at various lactate concentrations. Med Sci Sports Exerc
21. Imbeault P, Saint-Pierre S, Almeras N, Tremblay A. Acute effects of exercise on energy intake and feeding behaviour. Br J Nutr
22. Irving BA, Weltman JY, Brock DW, Davis CK, Gaesser GA, Weltman A. NIH ImageJ and Slice-O-Matic computed tomography imaging software to quantify soft tissue. Obesity (Silver Spring)
23. Irwin ML, Yasui Y, Ulrich CM, et al. Effect of exercise on total and intra-abdominal body fat in postmenopausal women: a randomized controlled trial. JAMA
24. Jakicic JM, Donnelly JE, Pronk NP, Jawad AF, Jacobsen DJ. Prescription of exercise intensity for the obese patient: the relationship between heart rate, V˙O2
and perceived exertion. Int J Obes Relat Metab Disord
25. Katzmarzyk PT, Church TS, Blair SN. Cardiorespiratory fitness attenuates the effects of the metabolic syndrome on all-cause and cardiovascular disease mortality in men. Arch Intern Med
26. Kohl HW, Blair SN, Paffenbarger RS Jr, Macera CA, Kronenfeld JJ. A mail survey of physical activity habits as related to measured physical fitness. Am J Epidemiol
27. Lee S, Kuk JL, Davidson LE, et al. Exercise without weight loss is an effective strategy for obesity reduction in obese individuals with and without type 2 diabetes. J Appl Physiol
28. Lohman TG, Roche AF, Martorell R. Anthropometric Standardization Reference Manual
. Champaign (IL): Human Kinetics Books; 1988. p. vi, 177.
29. Mitsiopoulos N, Baumgartner RN, Heymsfield SB, Lyons W, Gallagher D, Ross R. Cadaver validation of skeletal muscle measurement by magnetic resonance imaging and computerized tomography. J Appl Physiol
30. Nicklas BJ, Penninx BW, Cesari M, et al. Association of visceral adipose tissue with incident myocardial infarction in older men and women: the Health, Aging and Body Composition Study. Am J Epidemiol
31. O'Leary VB, Marchetti CM, Krishnan RK, Stetzer BP, Gonzalez F, Kirwan JP. Exercise-induced reversal of insulin resistance in obese elderly is associated with reduced visceral fat. J Appl Physiol
32. Pritzlaff CJ, Wideman L, Blumer J, et al. Catecholamine release, growth hormone secretion, and energy expenditure during exercise vs. recovery in men. J Appl Physiol
33. Pritzlaff CJ, Wideman L, Weltman JY, et al. Impact of acute exercise intensity on pulsatile growth hormone release in men. JAppl Physiol
34. Sallis JF, Haskell WL, Wood PD, et al. Physical activity assessment methodology in the Five-City Project. Am J Epidemiol
35. Seip RL, Snead D, Pierce EF, Stein P, Weltman A. Perceptual responses and blood lactate concentration: effect of training state. Med Sci Sports Exerc
36. Slentz CA, Aiken LB, Houmard JA, et al. Inactivity, exercise, and visceral fat. STRRIDE: a randomized, controlled study of exercise intensity and amount. J Appl Physiol
37. Slentz CA, Duscha BD, Johnson JL, et al. Effects of the amount of exercise on body weight, body composition, and measures of central obesity: STRRIDE-a randomized controlled study. Arch Intern Med
38. Stoudemire NM, Wideman L, Pass KA, McGinnes CL, Gaesser GA, Weltman A. The validity of regulating blood lactate concentration during running by ratings of perceived exertion. Med Sci Sports Exerc
39. Thamer C, Machann J, Stefan N, et al. High visceral fat mass and high liver fat are associated with resistance to lifestyle intervention. Obesity (Silver Spring)
40. Thomas EL, Bell JD. Influence of undersampling on magnetic resonance imaging measurements of intra-abdominal adipose tissue. Int J Obes Relat Metab Disord
41. Tremblay A, Despres JP, Leblanc C, et al. Effect of intensity of physical activity on body fatness and fat distribution. Am J Clin Nutr
42. Tremblay A, Simoneau JA, Bouchard C. Impact of exercise intensity on body fatness and skeletal muscle metabolism. Metabolism
43. Weltman A, Seip RL, Snead D, et al. Exercise training at and above the lactate threshold in previously untrained women. Int J Sports Med
44. Yoshioka M, Doucet E, St-Pierre S, et al. Impact of high-intensity exercise on energy expenditure, lipid oxidation and body fatness. Int J Obes Relat Metab Disord
Keywords:©2008The American College of Sports Medicine
PHYSICAL ACTIVITY; WEIGHT LOSS; METABOLIC SYNDROME; DIABETES; CARDIOVASCULAR; HUMAN